Emotion regulation flexibility and momentary affect in two cultures
Bibliographic record
Abstract
Abstract Recent theoretical models highlight the importance of emotion regulation (ER) flexibility, challenging traditional notions of universally maladaptive versus adaptive strategies. Here we employed ecological momentary assessment to develop proxy ecological measures for ER flexibility components (context sensitivity, repertoire and feedback responsiveness) and examine their associations with momentary affective outcomes in two independent samples from the United States (158 adults and 12,217 observations) and China (144 adults and 11,347 observations, analysis preregistered). Participants completed four daily surveys for 21 days, reporting emotional situations, situation characteristics, ER use and change and momentary distress. Increased momentary context sensitivity and use of repertoire were found associated with reduced distress, while results for feedback responsiveness were less consistent. Maintaining effective strategies was generally adaptive, whereas switching from ineffective strategies was adaptive for momentary depressed, but not anxious, mood. This innovative ecological momentary assessment design demonstrates transcultural similarities in ER flexibility’s benefits and nuanced implications of its components on affective outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".